摘要
本研究利用脚本语言编写一系列程序流程,成功对猪圆环病毒2型(PCV2)ORF1的Genbank数据进行快速整理和信息挖掘。同时,引入MUSCLE、MrBayes和PAML等生物信息学工具对经过整理的PCV2 ORF1的Genbank数据进行深度的分析,快速进行序列比对并获得了高解析度的BMCMC系统发育树,再以该BMCMC系统发育树为基础数据进行基因选择压力的分析。结果表明,中国的猪圆环病毒2型(PCV2)ORF1可分为三群,其中两群可能存在明显的祖先,另一群则可能经过多次从不同地方传入中国。另外,应用位点模型和分支位点模型(以不同的选择压力模型将不同群各设为背景)对PCV2 ORF1进行分析,没有发现各个分支上有明显处于正选择压力下的位点,PCV2的ORF1基因在进化上相当保守,所有位点的dN/dS值均小于等于1(P>95%),提示该基因没有处于明显的选择压力之下,所有位点的突变均为中性选择位点或净化选择位点。该结果首次从选择压力分析的角度说明ORF1基因为功能保守的基因,为以后筛选PCV2毒株制备抗ORF1蛋白的单克隆抗体提供了理论依据。
In this study,a set of programs were written by Perl script computer language.Based on these programs and Genbank data of ORF1 gene of PCV2,a model for quick data processing and data mining was established.Meanwhile,a set of bioinformatic softwares（like MUSCLE,MrBayes and PAML） were introduced to the deeper data analysis for PCV2 ORF1 gene,including the quick sequence multiple alignment,the reconstruction of the BMCMC phylogenetic tree and the BMCMC tree-based selective pressure analysis.The results indicated that ORF1 gene of Chinese PCV2 strains can be clustered into three lineages.Two lineages may have common ancestors and the other lineage may experience multiple introductions from different place and different time.Moreover,PAML site model and branch-site model（different lineages were set as background） were applied to do the selective pressure analysis for PCV2 ORF1 gene.The results revealed that there were no significant sites under positive selective pressure on ORF1 gene in different models.The ORF1 gene may evolve very conservatively and all the dN/dS values of different models were less than or equal to 1（P95%）,which suggested that the ORF1 gene didn＇t evolve under selective environments and all the amino acid residues were under neutral or purified selection.So the conservative evolutionary process of PCV2 ORF1 gene was revealed by the selective pressure analysis for the first time.This evidence may be helpful to the reference strains selection of PCV2 and thus the further preparation of the anti-ORF1 monoclonal antibody.
出处
《广东畜牧兽医科技》
2010年第5期35-41,共7页
Guangdong Journal of Animal and Veterinary Science
